Review of Population and Social Policy, No. 8, 1999, 75–115.

Population Projections for Japan: Methods,
Assumptions and Results
Shigesato TAKAHASHI, Ryuichi KANEKO, Akira ISHIKAWA,
Masako IKENOUE and Fusami MITA*

Abstract
The National Institute of Population and Social Security Research
officially announced a new round of population projections for Japan in January
1997. This article outlines the projection results and describes the methods used toobtain them. The projections, made following the release of 1995 census data,
provide three variants based on three different scenarios of fertility prospects:
medium, high, and low fertility variant projections. According to the medium
projection, the population of Japan will increase from 125.6 million in 1995 to apeak of 127.8 million in 2007, followed by a constant decrease to 100.5 million in
2050. The proportion aged 65 and over will expand from 14.6% in 1995 to 32.3%
in 2050. The projected loss of population and aging will be due mainly to thecontinuous below-replacement fertility rate during the past and coming decades.
The projections incorporated some factors of low fertility such as later and fewer
marriages. This article explains how the fertility and mortality prospects were
provided for the projections as well as the results of analyses on which theprospects were based.

1. Introduction
According to the population projections prepared by the National Institute ofPopulation and Social Security Research in 1997, the aging population in Japan
will reach a much higher level much faster than predicted in 1992. The difference
between the 1992 and 1997 projections is that the 1997 projection assumes a
relatively lower fertility rate. In particular, the declining fertility rate, which inrecent years has dipped below the population’s replacement level, apparently
will significantly increase the aging population and lead to a diminishedpopulation overall.
The results of the population projections are presented in section 2, together
with a summary of our method and assumptions. Detailed information on themethod and assumptions is provided in section 3.
This report includes population projections for Japan by age and sex for theyears 1995 to 2050. These numbers are based on an estimated 1 October 1995,
This is the English version of an article published in Jinko Mondai Kenkyu ( Journal of Population
Problems) 53 (1), March 1997.
* National Institute of Population and Social Security Research.

[ 75 ]

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Shigesato TAKAHASHI, Ryuichi KANEKO, Akira ISHIKAWA,
Masako IKENOUE and Fusami MITA

resident population consistent with the 1995 census as enumerated and areprojected forward using the cohort-component method with alternative
assumptions for future fertility, life expectancy, and net immigration levels. The
main projection period is taken to be 55 years up to the year 2050. The
projection for Japan has been carried forward for an additional 50 years up to theyear 2100 as a reference projection.
This projection includes three variants concerning the future trend in fertility
rates. The total fertility rate based on a medium variant assumption will decline
from 1.42 at the beginning of 1995 to 1.38 in 2000. Thereafter, a gradual upwardchange is predicted, and by 2030 the rate will be 1.61. Thereafter, the rate will be
constant. Population projections based on a high variant assumption indicate thatthe total fertility rate will turn upward beginning in 1997, and when it reaches
1.85 by 2030, it will maintain that level. The population projections based on a
low variant assumption show that the downward trend in the total fertility rate willcontinue until 2005, when it will reach 1.28, and thereafter, a slight upward
movement. It is predicted that even after the year 2030 it will cease at the 1.38 level.
For assumptions of survival rates, future life tables have been constructed. The
average life expectancies of both sexes, which in 1995 were 76.36 years for men
and 82.84 years for women, would continue growing constantly from thenonward: 77.40 years for men and 84.12 years for women in 2000, 78.80 and 85.83
in 2025, and 79.43 and 86.47 in 2050.
The assumption of net international immigration rates assumed that the recent
international net immigration rates would remain constant in the future as well.
To divide the future number of newborns into male and female, we need toestimate the sex ratio of births. Based on the sex ratios of previous births,
fluctuations on a yearly basis are negligible. For this reason, we assumed that themean value (105.6) of the sex ratios of births from 1991 to 1995 would also
remain constant from 1996 onward.

2. Projection Results
2.1. The Arrival of the Diminishing Population Era

According to the 1995 National Census, the starting point for our population
projections, the gross population of Japan was 125,570,000. From the findings ofthe population projection based on the medium assumption, the population will
gradually increase and reach 126,890,000 by the year 2000. It will then peak at
127,780,000 by 2007. Thereafter, it will continue to decline for a long period oftime (Fig. 1; see also Table A-3 in App.). In 2017 the population will nearly return

Population Projections for Japan: Methods, Assumptions and Results

77

to the 1995 level, and by 2050 it will diminish to 100,500,000. Furthermore, by
the year 2051, as a reference projection, and thereafter, the population willcontinue to decline, and at 2100 it will be sealed at 67,370,000.
Based on the population projection using the high variant assumption, thetotal population will peak at 129,560,000 by 2011, which is slightly behind the
medium variant assumption. Thereafter, the trend will decline, and in 2050 the
population will be reduced to 110,960,000. On the other hand, the low variant
assumption indicates that the population will peak at 127,050,000 by 2004 andthereafter continually decline to 92,310,000 by 2050.
Thus, as soon as the 21st century begins, the population of Japan will enter an
era of decline, ending the continuous increase in population. This historicchange has already affected the fertility rate (population replacement level, total
fertility rate—approx. 2.08 level) defined as maintaining the stationary populationlevel since the middle of the 1970s.
2.2. A Society with Fewer Children

The number of births in Japan decreased from 2,090,000 in 1973 to 1,190,000 in
1995. Based on the low birth prediction for the next few years, the child(1,000)140,000

120,000
Last time(Medium)

100,000

Highvariant
Mediumvariant

80,000Low variant

60,00040,000
ActualProjected

Reference projected

20,00001950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100

Figure 1 Actual and projected populations of Japan, 1950–2100

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Shigesato TAKAHASHI, Ryuichi KANEKO, Akira ISHIKAWA,
Masako IKENOUE and Fusami MITA

population aged 0–14 started to decrease from 27,000,000 beginning in 1980 (Fig.
2; see also Table A-3 in App.).
Whereas the 1995 National Census gave a child population of 20,030,000, themedium variant assumption shows that that population will decrease to
18,000,000 by 1999. Thereafter, until 2014, it will temporarily stabilize at around
18,300,000. However, after 2015 it will dip to the 18,000,000 level and gradually
decline for a long time. By the end of 2050 it is predicted that the childpopulation will be reduced to about 13,000,000. Based on the reference
projection of 2051 and thereafter, the long-term downward trend will continue.
The population will drop to 12,000,000 by 2059 and to below 10,000,000 by
2090. Indications are that it takes approximately one century to reduce the childpopulation to half its size.
In making assumptions about population trends, when examining the future
fertility rate according to high and low variants, the high variant assumption
shows that due to the second baby boom the child population will temporarily
decrease but will recover to 20,000,000 by the year 2010. Nevertheless, in thelong term the population will continuously decrease due to the low fertility rate.
(1,000)90,000Working-age
population(15–64)80,00070,00060,00050,00040,00030,000

ActualChild population(under 15)

Projected

Reference
projected

Aged population(65 and over)

20,00010,000Oldest population(75 and over)01950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100

Figure 2 Trends in major age composition of the total population:
Medium variant, 1950–2100

Population Projections for Japan: Methods, Assumptions and Results

79

The high variant assumption shows that at 2050 the population will reach
17,060,000, and then by 2100 it will decline to 14,770,000.
The low variant assumption shows that due to the extremely low fertility rate itis projected that the population will rapidly decline. The 1995 population level of
20,000,000 will drop to the 15,000,000 level by 2020. By the middle of the 21st
century the population will plummet to 10,000,000, which is one-half of the 1995
population. At the end of the 21st century it is projected to shrink to 6,600,000.
Thus, if the extremely low fertility rate continues to decline, the child population
cannot grow, and it is inevitable that Japan will have a diminishing population.
In considering the proportion of the total population to the child population,
however, the total population will not change significantly. The reason is that the
total population decreases simultaneously while the ratio of the child population
to the total population gradually decreases proportionally. The results of our
projections based on the medium variant assumption show that the proportion of
the child population will decline from 16.0% in 1995 to 14.3% in 2007, which will
see the peak population of Japan. Thereafter, the population will gradually falloff. By the middle of the next century the child population will settle at the13.11% level.
2.3. Aging of the Working Population

The working population, aged 15–64 years, has been consistently increasing
since World War II and, according to the 1995 National Census, reached87,260,000 in that year. Based on the results of the medium variant assumption,
since that population reached its peak in 1995, it has experienced a downward
trend. In 2030 it will drop below 70,000,000, and by 2050 it will fall to 50,000,000(Fig. 2; see also Table A-3 in App.). In particular, the population of new
graduates (aged 20–24) entering the workforce for the first time will rapidly
decline—from 99,100,000 in 1995 to 61,800,000 by 2025. After 2050, the absolute
number of the working-age population will continue to decrease as the low
fertility rate and the child population decline. By 2100, the final year of thereference population projection, it will reach 38,090,000, which is less than halfof the 1995 level.
In studying the differences in the fertility rate using the high and low variant
assumptions, the high variant indicates that the decline of the working-age
population is rather slow. It is projected to drop below the 70,000,000 level in2035 and thereafter will decline to 61,450,000 in 2050 and to 52,240,000 in 2100.
Based on the high variant assumption, over the long term the population will not
decline more than 50%. Still, it is indicative of a downward trend. The low
variant shows that the population will decrease below 70,000,000 in 2027 and80

Shigesato TAKAHASHI, Ryuichi KANEKO, Akira ISHIKAWA,
Masako IKENOUE and Fusami MITA(%)
70

Working-age
population(15–64)60

50
ActualProjected

Reference projected

40
Aged population(65 and over)30

20Child population(under 15)

10
Oldest population(75 and over)01950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100

Figure 3 Trends in the composition of the total population,by percentage or major age group

below 50,000,000 in 2050. By the year 2100 it will be curtailed at 27,760,00.
Thus, depending on the future trend in the fertility rate, the degree and rate of
decline of the working-age population will vary. However, assuming acontinuous decline in the fertility rate, a reduction in that population isinevitable. Such a change may result in a diminished labor force among young
people, an aging of the labor force, and a decline of the total labor force.
2.4. Arrival of an Advanced Aging Society

According to the medium variant, the child population will continue to decline.
Whereas the working-age population has started to decline, the aged population(over 65 years) will continue to increase significantly—from 18,000,000 in 1995 to
33,000,000 by 2025. Thus, a proportion of the population will increase from
14.6% in 1995 (1997) to 25% in 2015 (Fig. 3; see also Table A-3 in App.).
Although the aged population will keep approximately 33,000,000 people
between 2015 and 2050, due to the low fertility rate the proportion will increasePopulation Projections for Japan: Methods, Assumptions and Results

(%)
35

81

Low variant
Medium variant

30

High variant
25
Last time(medium)
20

15

10ActualProjected

Reference projected

501950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100

Figure 4 Trends in the percentage of the aged population:
Medium, high, and low variants, 1950–2100

by 2015 and thereafter. By 2050 the population will reach the 32% level.
After 2050 the aged population will begin to decline. Because of the projectedlong-term decline in the fertility rate, there will be fewer elderly people than in
the previous generation. Therefore, the population of the aged will also decline.
It is predicted that the aged proportion of the population will be slightly lower
than the 32% level of 2050, and that it will reach 28.8% in 2100.
In examining the differences in the aging trend based on assumptions of the
future fertility rate, there is a discrepancy of 1.7 points between the low variant(28.2%) and the high variant (26.5%) in 2025 (Fig. 4; see also Table A-3 in App.).
The differences indicate that the future fertility rate will have an impact on the
aging population, and the gap between the three variants will further widen over
the years. By 2050 there will be a gap of 6 points between the 29.2% high variant
and the 35.2% low variant. Thus, if the society maintains a low fertility rate for along period, the aged proportion of that society will continue to increase.

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Shigesato TAKAHASHI, Ryuichi KANEKO, Akira ISHIKAWA,
Masako IKENOUE and Fusami MITA

2.5. Changes in the Population Pyramid

The population pyramid of Japan indicates that the country’s overall population
will become aged because of the rapid increase and decrease of the past fertility
rates (e.g., first a baby boom—rapid growth of the fertility rate between 1947 and1949 and an echo effect—rapid decline of the fertility rate between 1950 and1957). Furthermore, the high and low birthrates repeatedly fluctuated thereafter.
Thus, the pyramid shows frequent ups and downs or rough contours (Fig. 5).
In the 1995 population pyramid, the first baby boom generation appeared in
the group aged 45–50, and the second baby boom generation appeared in thegroup aged 20–25. In 2025 the first-generation will reach ages 70–75, and thesecond generation will reach ages 50–55. The aging population up to the year
2050 is centered around the first generation baby boomers. On the other hand,the elevated aging level around 2050 was caused by the aging of the secondgeneration baby boomers. It was also affected by the continuously low fertility
rate. It indicates that the population will shrink in every generation. Thus, thepopulation pyramid of Japan will transform from the prewar shape of Mt. Fuji tothe shape of a temple bell in 1995 and to the shape of a vase in 2050.
2.6. Changes in the Population Dependency Ratio

The population dependency ratio is an index number to indicate the degree of theburden of support by the working-age population and compare the relative
differences between the child and the aged populations. The old-aged dependency
ratio based on the medium variant (value = aged population – working population)
will rise from 21% (4.8 workers to support 1 old-age dependent) in 1995 to 45% (2.2
workers to support 1 old-age dependent) in 2020 (Fig. 6; see also Table A-1 inApp.). By 2050 it is projected that the child dependency ratio (value = childpopulation – working-age population) will shift from the 1995 level of 23% (1 childdependent supported by 4.3 workers) to a range of 21% to 24%.
In spite of the declining child population due to the low fertility rate, thereason for the increasing (rather than declining) level of the child dependency
ratio is that the working population of the parents’ generation has been declining.
The population dependency ratio is defined as the sum of the child and oldage dependency ratios; it indicates relationships between the working populationand the degree of the total support. The overall population dependency ratio will
increase along with the old-age dependency ratio. Because the working-age
population is shrinking, it is projected that the population dependency ratio will
increase from 44% in 1995 to 78% by 2025; thereafter, it will reach the 83% levelin 2050.

Population Projections for Japan: Methods, Assumptions and Results

83(1) 1995
Age
100
95
90

Male

Female

85
80
75
70
65
60
55
50
45
40
35
30
25
20
15
10
5
120

100

80

60

40

20

0

0

0

20

40

60

80

100

120

Population (10,000)(2) 2025
Age
100
95
90

Male

Female

85
80
75
70
65
60
55
50
45
40
35
30
25
20
15
10
5
120

100

80

60

40

20

0

0

0

20

40

60

80

100

120

Population (10,000)(3) 2050
Age
100
95
90

Male

Female

85
80
75
70
65
60
55
50
45
40
35
30
25
20
15
10
5
120

100

80

60

40

20

0

0

0

20

40

60

80

100

120

Population (10,000)

Figure 5 Changes in the population pyramid: Medium variant, 1995, 2025, 2050

84

Shigesato TAKAHASHI, Ryuichi KANEKO, Akira ISHIKAWA,
Masako IKENOUE and Fusami MITA
(%)
90
80
Overalldependency ratio

70
60
50

Old-agedependency ratio

40
Child
dependency ratio

30
20
10

ActualProjected

Reference projected01950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100

Figure 6 Trends in age dependency: Medium variant, 1950–2100

2.7. The Impact of an Aging Society

The rising proportion of the population aged 65 and over, referred to as
population aging, is a central subject of research among social scientists. This isbecause, in every society, the socioeconomic effects of a growing aged
population is a critical issue for social policy. It is important for demographersand other scientists to study the effects of population aging and to offer guidance
to policymakers.

3. Projection Techniques and Assumptions
The future population size and its age-sex structure can be predicted if the future
number of deaths by age and sex, births with sex ratios, and rate of immigration
are all known. Therefore, the future population of Japan is projected byassuming its future mortality, fertility with sex ratios at birth, and rate ofimmigration from abroad.

Population Projections for Japan: Methods, Assumptions and Resultst

85

Population by age/sex in year t ; N(x,t )Female fertility rateby ageWorld immigration rate byage/sex

Sex ratio of births

Survival rate by age/sex

Year
Number ofbirths by sex

Age 0

t+1

Ages 1 to 100+
Population by age/sex in year t +1; N(x +1, t +1)

Figure 7 Procedures for projecting population

3.1. Projection Techniques

We adopted the usual cohort component projection method. This method starts
off with the population by age/sex as of a base year, then applies the assumed
survival rate by age/sex, international immigration rate by age/sex, and female
fertility rate by age, in addition to the sex ratio at birth, to determine the future
population. The basic calculation procedures for the cohort component method
are illustrated in Figure 7.
Let us, for example, calculate the population for the following year (t+1) fromthe known population by age/sex in year t. The population aged one-year old
and older in year t+1 can be found by applying the pertinent survival andinternational migration rates both by age/sex to the population in year t. The
female population multiplied by its age-specific fertility rate and sex ratio at birthyields the number of births by sex. We then apply to these numbers the survival
rate and the international immigration rate to find the population by sex underage one in year t+1. These values add up to the projected population in year t+1.
More specifically, as regards each population by age/sex from age 1 to 99 and“100 or over,” the population of age x is multiplied by the assumed survival rate

86

Shigesato TAKAHASHI, Ryuichi KANEKO, Akira ISHIKAWA,
Masako IKENOUE and Fusami MITA

for that age group, and is adjusted by the number of international immigrants
from age x to age x+1, to find the population of age x+1 on the following 1
October. For the population under age one, we find the average population of
females in the reproductive age period (15–49) during the base year. Then, we
multiply this value by the assumed rate of female age-specific fertility to find thenumber of births for one year. Next, we divide that number by using the sex
ratio at birth to get the sex breakdown. Finally, we multiply the figures by thesurvival rate (the probability that the newborns will live to the next year), andadjust for the number of international immigrations to determine the population
under age one on the following 1 October.
After repeating these procedures, we project the future annual population byage/sex. Therefore, the data needed for the cohort component method used inthis projection are (1) base population by age/sex, (2) the assumed female agespecific fertility rate, (3) the assumed survival rate by age/sex, (4) the assumed
rate of international immigration by age/sex, and (5) the sex ratio at birth.
3.2. Base Population

The base population, which is what we start with when making a population
projection, consists of the male and female population figures, classified by age
group (including non-Japanese residents) as of 1 October 1995. This population
is based on the 1995 national census with adjustments for the unknown age
population. Therefore, for each age group, there is a slight difference between
the values of the national census and the base population used in this projection.
3.3. Assumptions of Fertility Rates

When projecting a future population by means of the cohort component method,
the populations of coming generations start off with the number of live births foreach future year. The number of live births in each year is taken to be the total
number of babies to which females in the reproductive period (ages 15–49) givebirth in the year concerned. The number of live births by females in each age
bracket is calculated by multiplying the female population of each age group by
the age-specific fertility rate for the applicable age. The female population foreach age group in the future is calculated by applying its survival rate andinternational immigration rate to the base population (described in detail in thenext section). In this section we will discuss how to estimate female fertility rates
by age. However, the fertility rate estimates are based on several assumptions
about future marriages and births. For these assumptions to be accurate, we must
understand the recent fertility trends in Japan.

Population Projections for Japan: Methods, Assumptions and Results

87

3.3.1. Overview of Recent Fertility Trends and Future Prospects

The total fertility rate (TFR) in Japan has been declining since 1973.1 It showed atemporary increase between 1982 and 1984 but then continued to decrease. In
1989 it was 1.57, below the lowest recorded level in Japanese history in 1966, theyear of “Hinoeuma” (fiery horse). After that, it continued falling, with somefluctuations, to 1.42 in 1995 (Fig. 8).
The decreasing fertility rate in Japan is a direct result of the sharp decline in
the marriage rate of individuals in the childbearing years. This, in turn, resultsfrom the younger generation’s tendency to marry later in life and therefore its
tendency to remain unmarried during the reproductive ages. Of women in theirlate twenties, 80.3% were married in 1970, but only 49.6% in 1995. The
proportion of the divorced and widowed in a population may contribute to thedecrease in the proportion married in general. However, because the proportion
never married in this 35-year period soared from 18.1% in 1970 to 48.0% in 1995,
we can say that the sharp increase in the proportion never married has mostly
contributed to the decrease in the proportion married. (Yearly statistics of the
proportion never married by age group are shown in Fig. 9.) There are alsochanges in age at marriage behind the increase in the proportion never married.
In other words, since the mean age at first marriage for females increased

2.4

Total fertility rate

2.2
2.0
1.8
1.6
1.4
1.2
1.0
1960

1965

1970

1975

1980

1985

1990

1995

Figure 8 Annual fertility rate, 1960–1995
1

The TFR is the sum of female age-specific fertility rates in all reproductive ages (usually
between 15–49) observed in a given calendar year. These fertility rates are equivalent to theaverage number of live births that are expected if the females remain fertile according to thegiven age-specific fertility rates for that year.

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Shigesato TAKAHASHI, Ryuichi KANEKO, Akira ISHIKAWA,
Masako IKENOUE and Fusami MITA

substantially from 24.2 years in 1970 to 26.3 years in 1995, it is likely that theincrease in the proportion of women who remained single in their twenties canbe attributed to their tendency to marry later in life.
We can determine the actual magnitude of the effect of the decrease in the
proportion of married women on the fertility rate during these periods. Table 1
provides a decomposition analysis of the changes in TFRs between 1970 and
1995. The changes in TFRs are decomposed into changes caused by thedifferences in the proportion of married females and those caused by changes in
the fertility rate during marriage. Results of the decomposition according to age
group are also presented in the table.
According to these findings, the TFR from 1970 onward decreased in eachperiod, and notably the decomposition analysis reveals that effects from thechanges (decreases) in the proportion of married women were always greaterthan the effects from the changes in the marital fertility rate. In particular, themarital fertility rates from 1980 acted to increase the TFR. In other words, atendency toward fewer childbirths in this period resulted mainly from theincreasing proportion of unmarried people (especially in their twenties), but notfrom a declining fertility rate of married couples.

(%)
100
90
80

Proportion unmarried

70
60

15–19 years
20–24 years
25–29 years
30–34 years
35–39 years
40–44 years
45–49 years

50
40
30
20
10
0
1950

1955

1960

1965

1970

1975

1980

1985

1990

1995

Figure 9 Annual rate of unmarried women by age group, 1950–1995

Population Projections for Japan: Methods, Assumptions and Results

89

When forecasting future fertility rates in Japan, therefore, the key points are tosee how long and until when the tendency to marry late in life or not at all will
last, how far it will reach, and how much it will increase the proportion ofpeople who will never marry. It also seems likely that we will be required todetermine to what extent the total number of children for married couples(average number of live births produced by married couples in their lifetime),
which so far has been stable at about 2.2, will decrease due to the trend toward
later marriage. When we projected the population in this study, we also
conducted a detailed analysis of population statistics regarding these matters and,based on our findings, adopted a method by which assumptions can be madeabout the future behavior of marriage and fertility rates. An overview of this isprovided in section 3.3.3. First, however, let us explain how we obtained futureage-specific fertility rates for each year if such assumptions are made.
3.3.2. Projection Method for Age-Specific Fertility Rates

Future age-specific fertility rates in each calendar year can be found by
rearranging fertility rates for relevant female cohorts. Since the female fertility rate
at age x in a certain year is the fertility rate at age x of the female birth cohortborn x years ago, age-specific fertility rates at ages ranging from 15 to 49 in thatyear can be found as a set of fertility rates at the proper age of 35 cohorts born

Table 1 Decomposition of the changes in total fertility rates: 1970–1995
Year

1970

~

1980

~

1990

~

1995

Total fertility rates

2.13

→

1.75

→

1.54

→

1.42

Change

–0.39

–0.20

–0.12

Total (all ages)
15~19
20~24
25~29
30~34
35 and overEffects from changes in proportion married
–0.24
–0.36
–0.15
–0.01
–0.01
0.00
–0.14
–0.13
–0.02
–0.09
–0.20
–0.09
–0.01
–0.03
–0.04
0.00
0.00
0.00

Total (all ages)
15~19
20~24
25~29
30~34
35 and overEffects from changes in marital fertility
–0.14
0.16
0.03
0.01
0.00
0.00
0.01
–0.02
–0.02
–0.05
–0.01
–0.03
–0.07
0.14
0.04
–0.04
0.05
0.03

Note: Calculations are based on five-year groups.

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Shigesato TAKAHASHI, Ryuichi KANEKO, Akira ISHIKAWA,
Masako IKENOUE and Fusami MITA

15 to 49 years ago. In this projection, we estimate age-specific fertility rates foreach cohort and rearrange them into age-specific fertility rates for each calendar
year (cohort fertility rate method). The reason we first estimate cohort fertility
rates, instead of directly finding them for each calendar year, is that the age
pattern of fertility is generally more stable in a cohort context.
Fertility rates for a cohort are estimated by employing a suitable mathematicalmodel with several parameters that represent some features of marriage and birth
behavior. Specifically, the fertility rates are projected using a generalized loggamma distribution model, with parameters such as the female cohort’s mean
age at first marriage and those at birth by birth order, the proportion nevermarried by age 50, and the proportion having birth by birth order.2 This model
enables our projection system to express basic change patterns of cohort fertility,
such as a tendency to marry and bear children later in life (matching recent
trends in Japan), or future effects expected to result from an increase in the
proportion of never-married females.
A comparison of the predicted by this model with the actual values for agespecific fertility rates for three female birth cohorts appears in Figures 10–12. The
fertility rates are simulated according to birth orders (from 1st child to 5th childand later). As a sum, the age-specific fertility rates are obtained. When using data
available by 1995, actual fertility rates for up to age 45, age 35, and age 25,
respectively, can be obtained from (1) a cohort born in 1950; (2) a cohort born in
1960, and (3) a cohort born in 1970. In the case of (1), it is likely that fertility
process will have almost ended, so that the period to be projected by the model
is quite short. The groups in (2) and (3), however, are still in the process. As for2

In this model, the fertility rate ƒn for each birth order n is first given as a function of age x toform this expression:f n x =Cnλnb n Γ 1/λ

1
2
n

λ

2
n

λ –2
n

exp

1

x–un

λn

bn

–

1
λ

2
n

exp λ nx–unbnWhere ƒ¡ and exp are a gamma function and an exponential function, respectively. Cn cun cbn,
and λn are parameters of each birth order (n). This formation is an extended version of theexpression known as the Coale-McNeill Model, which is one of the generalized logarithm
gamma distribution formulas. The birth orders consist of five groups, the 1st through the 4thchild, and the 5th child and later. However, this method alone places a limit on the reproducible
ability of actual fertility rates by age. Therefore, through error analysis using the actual results offertility rates in Japan, we have modified it by extracting a standard error pattern (εn(x)).
As a result, ƒ(x), the fertility rate function by age of cohort, can be calculated using this expression:
5

f x =
n=1

f n x;Cn , un , b n , λ n + ε n x

For more details, see Ryuichi Kaneko, “A Projection System for Future Age-Specific Fertility
Rates” (in Japanese with English summary), Jinko Mondai Kenkyu ( Journal of Population
Problems), 49(1) (April 1993): 17–38.

Population Projections for Japan: Methods, Assumptions and Results

91

Total number of births

0.20

Actual values
Model values

Birthrate

0.15

1st child
2nd child

0.10

4th child
5th child or later0.05
3rd child

0.00
15

20

25

30

35

40

45

50

Age

Figure 10 Cohort birthrate by age and birthrate by age/birth order(actual values and estimates): Women born in 1950

0.20

Actual values
Total number of births

Model values

Birthrate

0.15

1st child

0.10

2nd child
4th child
0.05
5th child or later

3rd child

0.00
15

20

25

30

35

40

45

Age

Figure 11 Cohort birthrate by age and birthrate by age/birth order(actual values and estimates): Women born in 1960

50

92

Shigesato TAKAHASHI, Ryuichi KANEKO, Akira ISHIKAWA,
Masako IKENOUE and Fusami MITA

0.20

Actual values
Model values

0.15
Birthrate

Total number of births

0.10

1st child

4th child
2nd child

0.05

5th child or later
3rd child
0.00
15

20

25

30

35

40

45

50

Age

Figure 12 Cohort birthrate by age and birthrate by age/birth order(actual values and estimates): Women born in 1970

the group in (2), since the overall fitness of the simulated to the actual values isregarded as good, it is likely that future fertility rates (for subjects aged 36 andolder) will not divert much from the predicted values of the model, taking into
account the acknowledged stability of age patterns of fertility.
On the contrary, for cohort (3), it is hard to tell if its suitability to the entire
age range is good or not, judging from the comparison between the actual values
and the model to date. In fact, in the cases of (1) and (2), we can identify model
values (parameter values) using a formal statistical technique (maximum
likelihood estimation method), and the result is relatively stable. But in the caseof (3), the result from such a method is unstable, and it is more difficult tospecify a unique result. Obviously, this tendency is more remarkable in ayounger cohort with a shorter fertility experience. To estimate future fertility rates
for such a cohort, we should provide some external assumptions to make up for
its instability. In addition, for the younger cohort whose members are not yet 15
years old, it is impossible to determine the future values through statisticaltechniques, because actual values for fertility rates cannot be obtained at all.
Consequently, we end up providing such younger cohorts (and unborn cohorts)
with assumptions about their overall fertility. How to provide these assumptions
is discussed later (section 3.3.3).

Population Projections for Japan: Methods, Assumptions and Results

93

If age-specific fertility rates for a series of cohorts are estimated by the
aforementioned methods, age-specific fertility rates for each calendar year can beobtained by rearranging them according to age. For example, fertility rates fromages 15 to 49 in the year 2000 can be obtained by combining the fertility rates fora cohort of 15-year-olds born in 1985, a cohort of 16-year-olds born in 1984, and acohort of 49-year-olds born in 1951. With this combination, fertility rates in all
years of a projection period can be found.3 In Figure 13, actual values arecompared with the model values of fertility rates obtained from this combination.4
The cohort model birthrates at this stage do not account for any short-term
effect (period effect) that temporary socioeconomic fluctuations may have on
marriage rates and birthrates. Of course, it is extremely difficult to know what
temporary fluctuations might take place in the future. But it seems that current
fluctuations have affected the birthrate statistics for the next year, as well as forthe last few years. This period effect appears as differences between the model

0.20
Actual values

0.18

Model values
1985

0.16
0.14

1990

Birthrate

0.12
0.10
1995
0.08
0.06
0.04
0.02
0.00
15

20

25

30

35

40

45

50

Age

Figure 13 Comparison of actual values of birthrates with age andmodel values for 1985, 1990, 1995

3

4

Technically speaking, fertility rates by age of the population at age x of year t involve twocohorts, such as those who are born in year (t –x) and those born in year (t –x –1).
Since actual values of fertility rates are calculated using the mid-year population, they areslightly different from officially announced values which are calculated from population data asof 1 October 1995.

94

Shigesato TAKAHASHI, Ryuichi KANEKO, Akira ISHIKAWA,
Masako IKENOUE and Fusami MITA

values and the actual values in Figure 13. To handle this period effect for theprevious and next few years, a time series projection is made based on monthly
data of birthrates by birth order, and according to the results, the estimates fromthe cohort model are graduated. The estimates obtained by the projection
method are made significant on the premise that future values (assumed values)of parameters incorporated into a cohort are appropriate. The next section
explains how we set up these parameters.
3.3.3. Assumption of Fertility for Cohorts over an Extended Period
3.3.3.1. Method by Which Assumptions Are Made

The fertility level for a cohort is basically determined by the married females’
reproductive behavior, which in turn is affected by the first-marriage-rate
distribution by age for each live birth cohort. To estimate the fertility level that iseventually achieved, or TFRs for cohorts over an extended time, we must assume
the age-specific first-marriage rate for a target cohort. Then, from the age at firstmarriage and experience model for the total number of newborns that is
obtained from the assumed first-marriage rate and basic survey data on birthtrends in the past, we can determine the average number of live births formarried females of the birth cohort. However, since fertility is somewhat affectedby separation resulting from divorce and death after marriage, as well as children
born out of wedlock, we need to take into account the effect of the separationby-divorce-and-death index as a coefficient. In consideration of the above, theTFR for a long-term cohort can be calculated from the equation given in Table 2.
To use this equation, estimate (1) the proportion never married and the mean
age at first marriage for the target female birth cohort and (2) the average
number of births for a married woman by age at first marriage based on theestimated mean age at first marriage for the female cohort. Then (3) estimate thecoefficient for the divorce/death effect separately.

Table 2 Total fertility rate equation for a cohort
Completed Number of
Total Fertility Rate
Effect Coefficient= (1– Proportion Never Married) × Newborns of×of Cohortfor Divorce/Death
Married Couples
Note: The proportion never married is the proportion of singles at age 50 of the general population,and is calculated by subtracting the accumulated age value (accumulated first-marriage rates) of
the first-marriage rate by age from 1. The completed number of newborns for married couples isthe average number of births by married females by the age of 50. Also, the effect coefficient for
divorce/death represents the degree by which divorced and widowed persons effect thebirthrates, which can be estimated from the number of births from married couples obtained
from the total fertility rate for the cohort, and basic survey data on birth trends in the past.

Population Projections for Japan: Methods, Assumptions and Results

95

3.3.3.2. The Target Cohort

The cohort used for this research is comprised of subjects aged 15 as of 1995
(those born in 1980). This cohort was used because the marriage and birtheffects for this age group end when the subjects become 50 years old in the year
2030, allowing us to estimate future birthrates at least until that date. In addition,
the female subjects who were 15 years old in 1995 should behave according to
the recent changes in marriage and birth behavior. If a cohort of age 25 were thetarget cohort, the marriage and birth behavior from 2020 onward would be fixed.
On the other hand, if a cohort of age 5 were selected, it would be difficult toestimate the changes in marriage and birth behavior because the cohort would
exhibit such behavior in the remote future. Therefore, in this projection, thetarget cohort consists of subjects who were born in 1980.
3.3.3.3. Changes in a Cohort’s Mean Age at First Marriage and the Proportion Never Married

Before estimating the first-marriage rate for our target cohort born in 1980, we
calculated the age-specific first-marriage rate for each female cohort from 1935
onward. In calculating this rate, we took into account the delay in registration of
the number of first marriages obtained from vital statistics (Fig. 14).
Based on these first-marriage rates, we estimated the mean age at firstmarriage and the proportion never married for each cohort. When making theseestimates, we had to consider the cohorts whose marriage behavior has not

0.16
0.14
1940
1945
1950
1955
1960
1965
1970
1975

First-marriage rates

0.12
0.10
0.08
0.06
0.04
0.02
0.00
15

20

25

30

35

40

45

Age

Figure 14 First-marriage rates by age of female cohorts born in 1935 or later

96

Shigesato TAKAHASHI, Ryuichi KANEKO, Akira ISHIKAWA,
Masako IKENOUE and Fusami MITA
28

Average age at first marriage

27

26

25

Cohort born in 1935–46
Cohort born in 1947–60
Cohort born in 1961–65

24

23
4%

5%

6%

7%

8%

9%

10%

11%

12%

Proportion never married

Figure 15 Relationship between average age at first marriage andproportion never married for cohorts born in 1935 or later

ended. For example, the subjects born in 1960 were only 35 years old in 1995
and could undoubtedly marry after that. For the first-marriage rate distribution for
those aged 35 or older for this kind of birth cohort, we estimated the age
distribution for first marriages using a logarithm gamma model. The resultant
relationship between the average age at first marriage and the proportion nevermarried for each cohort born from 1935 to 1965 is shown in Figure 15.
Incidentally, the proportion never married is the remainder of the proportion
ever married figured as the accumulated age-specific first-marriage rates up to
age 50. The points marked by x in the figure are the mean age at first marriage
and the proportion never married for those who were born in 1935 to 1946.
Except for the two cohorts born in 1945 and 1946, these cohorts are stable in thatthey uniformly married at an early age. For example, their mean age at firstmarriage is about 24, and their proportion never married is over 4%. The bulleted
points in Figure 15 are the cohorts born from 1947 to 1960. Although thesegroups started exhibiting changes in marriage behavior from the late 1960s,
gradual increases in the mean age at first marriage and the proportion nevermarried are seen. Similar trends are also presumed for cohorts born from 1961 toPopulation Projections for Japan: Methods, Assumptions and Results

97

1965. Thus, we find that for females born in 1935 or later, the age at firstmarriage and the proportion never married tended to increase, while we see acertain change in the pattern from the baby boom generation onward.
Based on these trends, we conclude that the mean age at first marriage andthe proportion never married for the cohort born in 1980 will be an extension of
the trends in changes that have been shown by the previous birth cohorts.
3.3.3.4. Forecast of Marriage and Birth Parameters for Cohort Born in 1980

Although first-marriage rates by age for the cohort born in 1980 is an extensionof changes in the past, it is difficult to predict to what extent the average age atfirst marriage and proportion never married will reach. In this forecast, weestimated theoretically possible values at a variety of levels through separate
simulation of average age at first marriage and proportion never married for thecohort born in 1980.
When we observed age-specific first-marriage rates according to each cohortand calculated their growth rates, we paid attention to the fact that the rate ofincrease in first-marriages shows a strongly positive growth tendency at later ages
if negative growth rate is shown in the rate of increase in first marriages by age
for younger age groups. For this reason, when we look at a cohort born in 1970,
we find that the age-specific first-marriage rate up to age 25 has already beenobtained (Fig. 16). From the growth rate of age-specific first marriages in thepast, we assumed the age distribution when this first-marriage rate would recoverto grow in the future at various levels (Fig. 17). Then, we assumed that thegrowth rate of age-specific first marriages would converge toward zero for thecohort born in 1980. Based on this assumption, when we estimate age-specificfirst-marriage rates from 1995 onward using the growth rate of those rates, we
can estimate age-specific first-marriage rates for the cohort born in 1980, which
are classified according to recovery levels of the growth rate for the cohort bornin 1970.
In accordance with the aforementioned method, we can estimate the mean
age at first marriage and the proportion never married for the cohort born in
1980. This estimate is illustrated in Figure 18. As shown in this figure, there are
more cases of growth in age-specific first-marriage rates. That is to say, if the
proportion never married is low, the mean age at first marriage will increase
because first-marriage rates increase for older age groups. It is also likely that the
proportion never married tends to increase, since a large increase in the mean
age at first marriage is not produced on the grounds that a lot of first marriages
will not take place for older age groups if there are fewer cases of growth in
first-marriage rates.
We can obtain one point of intersection when plotting the theoretically98

Shigesato TAKAHASHI, Ryuichi KANEKO, Akira ISHIKAWA,
Masako IKENOUE and Fusami MITA

Growth rate of first marriages

0.10

0.05

1955–1960
1956–1961
1957–1962
1958–1963
1959–1964
1960–1965
1961–1966
1962–1967
1963–1968
1964–1969

0.00

–0.05

–0.10
15

20

25

30

35

40

Age

Figure 16 Growth rate of first marriages between cohorts,
1955–60 to 1964–69
0.08

Growth rate of first marriages

0.06

0.04

0.02

0.00

Patterns of assumed growth rates offirst marriages for 20-year-olds or older

–0.02

1
3
5
7

–0.04

2
4
6

–0.06
15

20

25

30

35

40

40

49

Age

Figure 17 Growth rate of first marriages assumed for the cohort born in 1970:
Levels from 1 to 7 of growth rates of first marriages

Population Projections for Japan: Methods, Assumptions and Results

99

28.0

Average age at first marriage

27.8

1
27.6

2
3
4

27.4

5
6
7

27.2

27.0
4% 5% 6% 7% 8% 9% 10% 11% 12% 13% 14% 15% 16% 17% 18% 19% 20%
Proportion never married

Figure 18 Estimated values of average age at first marriage and proportion
never married for the cohort born in 1980, which are assumed fromthe growth rate of first marriages at levels from 1 to 7

possible relationship between the mean age at first marriage and the proportion
never married for the cohort born in 1980 and the relationship between theobserved mean age at first marriage and the proportion never married for thecohorts born in 1953 and later on the same graph (Fig. 19). This point ofintersection is a combination of the expected mean age at first marriage and the
proportion never married for the cohort born in 1980, which is determined by
the trends in mean age at first marriage in the past.
In this projection, we assumed from this point of intersection that the mean
age at first marriage of the target cohort born in 1980 was 27.4 years and the
proportion never married was 13.8%. This assumption serves as the basic value
when making an assumption for birthrates at the medium level. In addition,
because there are considerable uncertain elements in the trends of mean age atfirst marriage and proportion never married, we make three kinds ofassumptions: for medium, high, and low levels.
To estimate the low level of fertility rates for the cohort born in 1980, we madean assumption about marriage based on experience in a region where the100

Shigesato TAKAHASHI, Ryuichi KANEKO, Akira ISHIKAWA,
Masako IKENOUE and Fusami MITA
30

Average age at first marriage

29

28

27

26

25

24

Assumption at low level: average age at first marriage(28.9 years) and proportion never married (17.9%) of
female graduates of 2-year-or-more colleges in Tokyo
Potential level of average age at first marriage
and proportion never married for thegeneration born in the 1980s

Assumption at high level: average
age at first marriage (25.7 years)
and proportion never married(8.3%) for the generation bornin the 1960s
Assumption at medium level: average age
at first marriage (27.4 years) andproportion never married (13.8%)

Relationship between average age at firstmarriage and proportion never married
based on trends in past generations

23
4% 5% 6% 7% 8% 9% 10% 11% 12% 13% 14% 15% 16% 17% 18% 19% 20%
Proportion never married

Figure 19 Relationship between average age at first marriage andproportion never married for a cohort born in 1980

tendency to marry later in life will become pronounced and the proportion nevermarried will increase to the largest possible level. As the female population ofTokyo that graduated from college or other higher educational facility (graduatesof 2-year colleges and 4-year-or-more universities) has the highest mean age atfirst marriage among various conceivable socioeconomic groups in Japan, we
assumed that the cohort born in 1980 throughout the country would display
similar marriage behavior to that of college graduates in Tokyo. From thisassumption, we derive their mean age at first marriage as 28.9 years and the
proportion never married as 17.9%.
At the high level it is assumed that there will be fewer changes in marriage
behavior, which is contrary to the assumption at the low level. Here, we
supposed that no change would occur for the cohorts born in 1961 or later, on
the assumption that the estimated mean age at first marriage was 25.7 years ofage and proportion never married was 8.3% for the cohort born in 1960.
After estimating the mean age at first marriage for medium, high, and low
levels of fertility, we considered the number of children born according to
distribution of age at first marriage for the cohort born in 1980. The total numberof children born on the average in terms of age at first marriages can be modeled

Population Projections for Japan: Methods, Assumptions and Results

101

Total number of newborns (on average)

3.0

2.5

2.0

1.5

7th survey
8th survey
9th survey
10th survey

1.0

0.5

0.0
~20

21~22

22~23

24~25

26~27

28~29

30~31

32~33

34~35

36~

Age at first marriage of wife

Figure 20 Total number of newborns on average according
to age at first marriage from individual studies:
Basic surveys (7th to 10th) on birth trends

as a stable relationship from the basic survey data for birth trends in the past
(Fig. 20). This model assumes that the number of births produced by married
women for the cohort born in 1980 were 1.96 children at the medium level, 2.12
at the high level, and 1.76 at the low level.
Calculation of the TFR for the entire cohort born in 1980 took into account the
proportion of those who remained single for life, as well as the effect of birth
behavior after the first marriage, which was influenced by separation resulting
from divorce or death of either husband or self. The influence exerted byseparation resulting from divorce or death indicated a stable trend, extrapolatingfrom basic survey data on birth trends and vital statistics from the past. Therefore,
we assumed 0.945 as the coefficient for the divorce/death effect in this estimate.
3.3.3.5. Assumed Values of Cohort’s Birthrate

TFRs for the cohort born in 1980 at each of three levels, which are found fromthe equation in Table 2 based on the proportion never married, mean age at firstmarriage, the total number of children of married couples and the adjustment
factor for the effect of divorce/death established by the aforementioned
procedures are 1.61 for the assumption at the medium level, 1.85 for the102

Shigesato TAKAHASHI, Ryuichi KANEKO, Akira ISHIKAWA,
Masako IKENOUE and Fusami MITA

assumption at the high level, and 1.38 for the assumption at the low level. The
assumed values and TFRs for this cohort are summarized in Tables 3 and 4.5
3.3.4. Projected Fertility Rate

The annual statistics of future TFRs that have been estimated by the threeassumptions used in this study are illustrated in Fig. 21 (see also Table A-1 inApp.). According to the estimate based on the assumption at the medium level,
the TFR would decrease to 1.38 in 2000 from 1.42 in 1995, then slowly increase
to 1.61 in 2030 and finally settle at a constant level from then on. In the case of
the estimate based on the assumption at the high level, the TFR would start
increasing from 1997 to 1.85 in 2030, then remain constant at this level. In thecase of the estimate based on the assumption at the low level, the decreasing
trend in recent years would continue until 2005, when the TFR would decrease
to 1.28, then slowly increase, but remain at 1.38 from 2030 on.

Table 3 Assumed variables for marriage and birth as well as total fertility rates
for female cohort born in 1980
Proportion
Completed Number Effect CoefficientLevel of
Average Age at
Cohort’s Total
Never Marriedof Newborns offorAssumption
First Marriage
Fertility Rate(%)
Married Couples
Divorce/Death
Medium

13.8

27.4

1.96

0.954

1.61

High

8.3

25.7

2.12

0.954

1.85

Low

17.9

28.9

1.76

0.954

1.38

Table 4 Assumed total fertility rates and distribution of quantity oflive births for female cohort born in 1980
Distribution of Quantity of Live Births (%)

Level of
Assumption

Cohort’s Total
Fertility Rates

None

1 Birth

2 Births

3 Births

4 Births

5 Birthsor moreMedium

1.61

23.0

15.9

42.2

15.5

2.8

0.6

High

1.85

14.0

15.4

47.0

19.4

3.4

0.8

Low

1.38

32.4

15.8

36.2

12.7

2.3

0.5

5

However, as described in section 3.3.2, the fertility rates for the cohort are also slightly different
from these values because the period effect is added to the finally estimated fertility rates forthe future.

Population Projections for Japan: Methods, Assumptions and Results

103

4.0
3.5
ActualTotal fertility rate

3.0

Projected

2.5
2.0High variant

1.5

Medium variant
Low variant

1.0
0.5
0.0
1950

1960

1970

1980

1990

2000

2010

2020

2030

2040

2050

Figure 21 Annual statistics for total fertility rates at medium, high,and low levels, 1950–2060

3.4. Assumptions for Survival Rates (Future Life Table)
3.4.1. Estimation Methods

To estimate the population of the following year based on the existing
population of a given year, we must know the survival rate by age and sex. For
this purpose, we need to prepare a future life table. The demographic methods
currently used to develop such a table include (1) constructing a model life table,(2) constructing a best life table, (3) extrapolating age-specific death rates, (4)extrapolating cause-specific mortality by age, (5) extrapolating standardized
cause-specific mortality, or (6) employing the relational model method.6
The model life table, the first method, is used to predict the average life
expectancy for countries where life expectancy is relatively short and mortality
data are inadequate. This method would be limited in terms of accuracy if used
to prepare a future life table for Japan. The best life table, the second method,

6

For future life tables, see Jyumyougaku Kenkyukai, “Life Span,” Seimeihyou no Shorai Suikei Shiryo(Estimated Data of the Future Life Table) 13, (September 1988); W. Brass, “On the Scale ofMortality,” in W. Brass, ed., Biological Aspects of Demography (London: Taylor and Francis, 1971);
A. J. Coale and P. Demeny, with B. Vaughan, Regional Model Life Tables and Stable Populations,
2nd edition (New York and London: Academic Press, 1983); and L. Heligman and J. H. Pollard,“The Age Pattern of Mortality,” Journal of the Institute of Actuaries 107(434), Part 1 (1980): 49–80.

104

Shigesato TAKAHASHI, Ryuichi KANEKO, Akira ISHIKAWA,
Masako IKENOUE and Fusami MITA

was previously used by the National Institute of Population and Social Security
Research to make population projections; it is based on the lowest actual agespecific death rates collected from life tables classified by country and region(prefecture). A best life table prepared in this way can provide practical target
values inasmuch as such tables are also used for other populations. This method
has been used in international population estimates developed by the United
Nations to obtain target life tables for countries where the average life
expectancy is longer than usual. However, even though the best life table can bea highly practical life table, it is impossible to determine the point in time when it
can be put into practice. Therefore, predictions about changes in life span must
be made separately. And for the estimates prepared by the United Nations, futurelevels of average life expectancy are also estimated separately. For these reasons,the best life table has been used only to determine death patterns by age.
Because the average life expectancy in Japan has already reached one of the top
levels in the world, a best life table based on a life table by country cannot be
used. For reference purposes, the best life table prepared using the life tableclassified by administrative divisions of Japan (1990) shows average life
expectancies of 78.57 years (males) and 85.13 years (females), which represent
increases of 2.21 years (males) and 2.29 years (females) compared with thecorresponding levels for 1995.
The third method—extrapolating age-specific death rates—involves finding a
constant time-wise law by applying trend lines to changes in age-specific death
rates, then using predictions of age-specific death rates in the future after theelapse of a certain period, which are made by extrapolating the law to the futurecases. In this method, a life table for any given time can be prepared. We used
this method in our population projections for the 1981 revision.
The fourth and fifth methods-extrapolating cause-specific mortality by age andextrapolating standardized cause-specific mortality-are basically extended
versions of the third method, by which future death rates by cause of death are
estimated. When observing the death rates according to cause of death, thesemethods have the advantage of being able to more easily obtain a curve
extending time series data (as opposed to when the curve is extended using only
age-specific death rates) and to reflect various features of each cause of death.
But the fourth method, in which the death rate is extrapolated and extended
based on cause of death and age, requires estimating about 468 curves for both
sexes (two classifications), ages (18 age classifications in increments of 5 years),and causes of death (13 classifications). Therefore, this method tends to becomecomplicated, and it cannot always obtain stability and regularity because somecauses of death consist of only a few cases. The fifth method is a simplified
version of the fourth, by which future parameters of standardized age mortality

Population Projections for Japan: Methods, Assumptions and Results

105

are found for each cause of death, and then future age-specific death rates are
estimated by applying the parameters uniformly to cause-specific mortality foreach age. This method was used for our population projection made in 1986 andthe previous estimate in 1992.
Whereas the third to fifth methods are designed to prepare a future life tablebased on the extension of time series data, the sixth method-the relational model
method-expresses age patterns of standard death rates using several parameters,
and a life table of death standards at any given level is prepared through conversionof the parameters. However, this method requires estimating future values for eachparameter separately. Currently, there are also problems ensuring accuracy.
For this study, we improved the “extrapolating standardized cause-specificmortality” method that was used for the previous estimate and then prepared afuture life table, taking into account the evaluation of each method.
3.4.2. Factors Influencing Average Life Expectancy Growth in Recent Years

The average life expectancy for both sexes in Japan increased all at once by about
15 years-from 50.1 to 65.3 years for males and from 54.0 to 70.2 years for femalesbetween 1947 and 1960, then leaped to the levels of other advanced countries. This
mainly resulted from the fact that the number of infant deaths due to infectious
diseases such as pneumonia, bronchitis, and gastroenteritis had decreased rapidly
and young deaths caused by tuberculosis had been virtually wiped out.
The average life expectancy then increased slowly but steadily, reaching 76.36
years for males and 82.84 years for females in 1995. In considering how muchthe decreasing death rate of different age groups contributed to an increasing life
span during 1955 to 1995, it was found that the decrease in the death rate ofyounger age groups, especially infants and young children, had been declining
year after year, whereas the death rates of middle-age-or-older population had
been on the increase. In terms of the growth of average life expectancy from1990 to 1995, it is recognized that 49.8% of males and 89.3% of females making
up the growth rates resulted from decreases in the death rate of those aged 65
and older.
In recent years, the major causes of death have included the three top adultdiseases: malignant neoplasm, cerebrovascular disease, and cardiac disease.
Among these, however, deaths resulting from cerebrovascular disease havedecreased rapidly—both in men and women. And in examining trends over the
past 20 years (1975–1995), from the viewpoint of standardized death rates (per100,000) for those aged 65 and older, we see that the rates decreased by about
30%—from 2,322 to 675 for males and from 1,985 to 641 for females. Cardiac
disease has also declined since the 1970s. On the other hand, malignant
neoplasm has decreased in women but increased in men.

106

Shigesato TAKAHASHI, Ryuichi KANEKO, Akira ISHIKAWA,
Masako IKENOUE and Fusami MITA

3.4.3. Assumptions of Death Rate (Future Life Table and Survival Rates)

The extrapolating standardized cause-specific mortality method, which was
adopted for our previous estimate, consists of extrapolating standardized death
rates for all age groups to each cause of death and then preparing a life table usingthat extrapolated data. But in this estimate, we adopted the method by which thestandardized cause-specific mortality is classified according to age, its future values
are estimated, and a future life table is prepared by converting the future values todeath rates by age. Specifically, we employed the following procedures.
First, to observe fluctuating trends in cause-specific mortality by age up to1995, we determined cause-specific median mortality by sex/age, classified inincrements of 5-year age groups (death rates where the mid-year population isthe denominator) for the 20 years from 1975 to 1995. The causes of death weredivided into 13 categories: (1) tuberculosis, (2) malignant neoplasm, (3) diabetes,(4) cardiac disease, (5) hypertensive disease, (6) cerebrovascular disease, (7)pneumonia and bronchitis, (8) gastric ulcer and duodenal injury, (9) chronic liverdisease and hepatic cirrhosis, (10) nephritis, nephrotic syndrome, and nephrosis,(11) accidents, (12) suicide, and (13) others.
Second, based on the 5-year age groups, we calculated standardized causespecific mortality for four age categories where the Japanese population by
sex/age group in 1990 (median population) served as the standard. In
considering levels of death rates, differences in fluctuations, and so on, we
decided on 4 age categories: 0 to 14 years, 15 to 39 years, 40 to 64 years, and 65
years and older.
Suppose the standardized mortality for age category (A) and cause of death (i)in year t is d s(i,A,t). Then, we apply a standard curve, based on the standardized
cause-specific mortality by sex/4 age categories for 1975 to 1995 (d s(i,A,t)),which has already been obtained for applicable cases, and extrapolate it to futureyears up to 2050. The applied curve could be an exponential curve, corrected
exponential curve, logistics curve, and so forth. Furthermore, to determine theexponent based on the standardized mortality in 1995 for 1996 to 2050, thedetermined exponent of age category (A) and cause of death (i) in year t shouldbe θ(i,A,t) (= d s(i,A,t)/d s(i,A,t0)). Here, t0=1995.
Meanwhile, we determine the total cause-specific death rates for each age for1992 to 1994 from the number of deaths for each age/cause of death for both
sexes. Suppose that the number of deaths for age x is D(x) and the number ofdeaths resulting from cause of death (i) is D(i,x). We then determine the causespecific death proportion M(i,x) from D(i,x)/D(x).
Based on the aforementioned values, we determine the survival probability foreach age p'x (t) in future year t from the following expression:

Population Projections for Japan: Methods, Assumptions and Results

P' x t =ΠP x t 0

107

M i,x ⋅θ i,A,t

Incidentally, we determine px(t0) from lx+1/lx through the use of the numberof survivors (lx) based on the simplified life table for 1995. However, because
people aged 95 and older are generalized as a single set of data in the simplified
life table, we determined several functions by extrapolating death rates (qx) ofolder age groups to the group of 95-year-olds and older by means of a corrected
exponential curve. Then we prepared a life table for up to age 100 and made it areference life table. In addition, because the calculated p'x (t) is the result on
which tendencies for each age category are reflected, unnatural trend lines are
created at the beginning and ending ages in the age category. For this reason, we
determine death rates by age qx (t) by graduating q'x(t) (=1–p'x(t)).
Then, depending on how you want to prepare the life table functions, use thefollowing expressions:l x+1 t =l x t × 1–q x t
l t +l x+1 t
Lx t = x2
However, we estimated L0 (t) and e100(t) separately, as follows.
To L0(t), we applied the corrected exponential curve of the average survival
years of those who died at age 0, f0=(L0-l1)/d0 for 1975 to 1995 and determined
f0(t) for 1996 to 2050. Then, to find L0(t), we calculated:

L 0 t =l 1 t +f 0 t ×d 0 t
To e100(t), we applied the corrected exponential curve based on actual values
for 1960 to 1995, then calculated:0ΣL 100 t =l 100 t ×e 100 t
T x t =ΣL x t
0e 0 t =T x t /l x t
3.4.4. Estimated Results of the Future Life Table

The average life expectancy by sex based on the estimated future life table isillustrated in Figure 22 (see also Table A-2 in App.). Based on this figure, the108Shigesato TAKAHASHI, Ryuichi KANEKO, Akira ISHIKAWA,
Masako IKENOUE and Fusami MITA

average life expectancy of both sexes, which was 76.36 years (males) and 82.84
years (females) in 1995, would continue growing constantly from then onward to
77.40 (males) and 84.12 (females) in 2000, 78.80 (males) and 85.83 (females) in
2025, and 79.43 (males) and 86.47 (females) in 2050. The difference between
males and females—6.48 years in 1995—would increase gradually to 6.71 in
2000, 7.03 in 2025, and finally settle at 7.04 from then on. The reason for thecontinuing difference between the sexes is that women initially live longer andmen show a somewhat slower growth in life span.
The survival rate ranging from birth to 20 years old was 98.9% (males) and
99.2% (females) in 1995 and would increase to 99.2% (males) and 99.5%(females) in 2050. The survival rate up to age 65 was 83.2% (males) and 91.6%(females) in 1995 and would reach 86.9% (males) and 94.8% (females) in 2050.
Considering the contribution of the decrease in the death rate by age to thegrowth of average life expectancy, it is recognized that the contribution made by
the 0 to 14 age group is low and will continue to decline, whereas the contributionof the middle-age-or-older age group, especially those who are in the prime of life
(aged 40 to 64 years), is high and will have a greater effect on growth.
(Age)
90
85
80

Females

Average life expectancy

75
70
Males
65
60
ActualProjected

55
50
45
40
1940 1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050

Figure 22 Annual statistics of average life expectancy: Actual andestimated values, 1940–2050

Population Projections for Japan: Methods, Assumptions and Results

109

For the three top adult diseases (malignant neoplasm, cerebrovascular disease,and cardiac disease), according to the standardized death rates (per 100,000) of
those aged 65 and older, it was likely that malignant neoplasm cases would
continue increasing to 1,511 (males) and 734 (females) in 2050 from 1,456 (males)
and 707 (females) in 1995. In the meantime, the instances of cerebrovasculardisease and cardiac disease would decrease; in particular, cerebrovascular disease
would show a noticeable improvement and decline by almost half or more in 2050.
3.5. Assumptions about the International Immigration Rate

For the future international immigration rate, we determined a mean value forexcess immigration rates by sex/each age (=[number of immigrants – number of
emigrants]/population) from 1990–1995 and assumed that this mean value would
remain invariant from 1996 onward.
In recent years, the immigration rate for Japan has been undergoing
considerable changes as the Japanese society has been internationalized andeconomic activity has fluctuated. According to the number of excess immigrants
shown in the emigration and immigration control statistics of the Ministry ofJustice, emigrants exceed immigrants in the Japanese population, whereas
immigrants exceed emigrants in the foreign population. Over time the tendencyof emigration and immigration of the Japanese population has been unstable andhas not shown a particular trend. On the other hand, excess immigrants for theforeign population have declined annually since 1991, when they were at theirpeak (57,000 people were recorded as excess immigrants), and there were only a
few of them in 1995. As a result, most of the excess emigrants in recent years
have come from the Japanese population and there has been no particular trend.
In terms of recent differences in the number of immigrants and emigrants
classified by age, it is difficult to predict the future because their levels havevaried from year to year and their trends have remained irregular. In addition, theinternational immigration rate depends on changes in government policy (such as
amendments to the immigration law). Because it is also affected by fluctuations ineconomic activity (business activity) and international circumstances, it is difficult
to predict only from past trends.
Consequently, in this estimate we assumed that the recent international immigration
rates would remain constant in the future as well. Specifically, we determined a meanvalue of excess immigration rates by age/sex for a recent 5-year period (1 October
1990–30 September 1995) that were listed in the “Currently Estimated Population”
from the Statistics Bureau of the Management and Coordination Agency andassumed that it would remain constant from 1996 onward (Fig. 23).

110

Shigesato TAKAHASHI, Ryuichi KANEKO, Akira ISHIKAWA,
Masako IKENOUE and Fusami MITA
(%)
1.5
1.0
Females
0.5

Excess immigration rate

0.0
–0.5

Males

–1.0
–1.5
–2.0
–2.5
–3.0
–3.5
0

10

20

30

40

50

60

70

80

90

Age

Figure 23 Excess immigration rates by age/sex: Average rates, 1991–1995

3.6. Sex Ratio of Births

To divide the future number of newborns into male and female, we need toestimate the sex ratio of births (=number of male births/number of female births
× 100). According to past sex ratios of births, fluctuations on a yearly basis are
negligible. For this reason, in this estimate we assumed that the mean value(105.6) of the sex ratios of births from 1991 to 1995 would also remain constantfrom 1996 onward (Fig. 24).

Population Projections for Japan: Methods, Assumptions and Results

111

110
109
108
Sex ratio of births

107
106
105
104
103
102
101
100
1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995

Figure 24 Annual statistics for sex ratio of births, 1985–1995

3.7. Assumed Values for the Long-range Population Projection

For the long range projection for 2051 to 2100 (the results are presented in
Figures 1 through 4 and 6, we made the following assumption:
In accordance with practices for the long-range population projection of theUnited Nations, we assumed that the fertility rate would gradually increase fromthe level in 2050 to 2.07 (population replacement level based on mortality levelof 2050) in 2150 for each of the medium, high, and low variants. We determinedthat the survival rate would settle at a constant level from 2050 onward, and sex
ratios of births and international immigration rates would remain unchanged
from the assumed values for 1996.

112

Shigesato TAKAHASHI, Ryuichi KANEKO, Akira ISHIKAWA,
Masako IKENOUE and Fusami MITA

Appendix
Table A-1 Actual and assumed total
period fertility rate under
the three variants

Table A-2 Actual and assumed life
expectancy at birth

Variant(Years)Year

Medium

High

Low

Year

Male

FemaleDifference

1995*
1996
1997
1998
1999

1.42170
1.42151
1.39656
1.38530
1.38001

1.42170
1.42151
1.42620
1.44524
1.470121.42170
1.42151
1.379031.35025
1.32764

1995*
1996
1997
1998
1999

76.36
77.02
77.12
77.22
77.31

82.84
83.59
83.73
83.87
83.99

6.48
6.57
6.61
6.65
6.68

2000
2001
2002
2003
2004

1.37987
1.38393
1.391311.40124
1.41306

1.499191.53074
1.56327
1.595451.62632

1.31050
1.29801
1.28936
1.28387
1.28105

2000
2001
2002
2003
2004

77.40
77.49
77.57
77.65
77.73

84.12
84.23
84.34
84.45
84.54

6.71
6.74
6.77
6.80
6.82

2005
2006
2007
2008
2009

1.42630
1.440451.455161.47005
1.48475

1.65537
1.682121.70628
1.72782
1.74684

1.28053
1.28203
1.285311.290101.29612

2005
2006
2007
2008
2009

77.80
77.87
77.93
78.00
78.06

84.64
84.73
84.81
84.90
84.97

6.84
6.86
6.88
6.90
6.91

2010
2011
2012
2013
2014

1.498901.512211.52449
1.535631.54634

1.763451.777811.790171.80071
1.810151.303091.310641.318421.326121.33394

2010
2011
2012
2013
2014

78.12
78.18
78.23
78.29
78.34

85.05
85.12
85.18
85.25
85.31

6.93
6.94
6.95
6.96
6.97

2015
2016
2017
2018
2019

1.55662
1.56624
1.57494
1.582451.58851

1.81862
1.82606
1.832431.83765
1.84170

1.34169
1.349071.35575
1.361441.36602

2015
2016
2017
2018
2019

78.39
78.43
78.48
78.52
78.57

85.37
85.42
85.48
85.53
85.58

6.98
6.99
7.00
7.00
7.01

2020
2021
2022
2023
2024

1.59335
1.597221.60028
1.60271
1.60460

1.84480
1.847171.848971.85032
1.85133

1.369641.37249
1.37471
1.37641
1.37770

2020
2021
2022
2023
2024

78.61
78.65
78.69
78.73
78.76

85.62
85.67
85.71
85.75
85.79

7.01
7.02
7.02
7.03
7.03

2025
2026
2027
2028
2029

1.60607
1.60720
1.608071.60873
1.609221.85208
1.85263
1.85303
1.853311.85352

1.37866
1.37936
1.37986
1.380221.38048

2025
2026
2027
2028
2029

78.80
78.83
78.87
78.90
78.93

85.83
85.87
85.90
85.94
85.97

7.03
7.03
7.04
7.04
7.04

2030
2031
2032
2033
2034

1.60960
1.60960
1.60960
1.60960
1.60960

1.85367
1.85367
1.85367
1.85367
1.85367

1.38066
1.38066
1.38066
1.38066
1.38066

2030
2031
2032
2033
2034

78.96
78.99
79.02
79.05
79.08

86.00
86.03
86.06
86.09
86.24

7.04
7.04
7.04
7.04
7.04

2035
2036
2037
2038
2039

1.60960
1.60960
1.60960
1.60960
1.60960

1.85367
1.85367
1.85367
1.85367
1.85367

1.38066
1.38066
1.38066
1.38066
1.38066

2035
2036
2037
2038
2039

79.10
79.13
79.15
79.18
79.20

86.15
86.17
86.20
86.22
86.24

7.04
7.04
7.04
7.04
7.04

2040
2041
2042
2043
2044

1.60960
1.60960
1.60960
1.60960
1.60960

1.85367
1.85367
1.85367
1.85367
1.85367

1.38066
1.38066
1.38066
1.38066
1.38066

2040
2041
2042
2043
2044

79.23
79.25
79.27
79.29
79.31

86.27
86.29
86.31
86.33
86.35

7.04
7.04
7.04
7.04
7.04

2045
2046
2047
2048
2049

1.60960
1.60960
1.60960
1.60960
1.60960

1.85367
1.85367
1.85367
1.85367
1.85367

1.38066
1.38066
1.38066
1.38066
1.38066

2045
2046
2047
2048
2049

79.33
79.35
79.37
79.39
79.41

86.37
86.39
86.41
86.43
86.45

7.04
7.04
7.04
7.04
7.04

2050

1.60960

1.85367

1.38066

2050

79.43

86.47

7.04

* Actual* Actual

Population Projections for Japan: Methods, Assumptions and Results

113

Table A-3 Projected future population and proportion by age group,
1995–2050: Medium variant
Year

Population (1,000)

Proportion (%)

Total

0–14

15–64

65+

0–14

15–64

65+

1995
1996
1997
1998
1999

125,570
125,869
126,156
126,420
126,665

20,033
19,707
19,40019,09918,821

87,26087,15887,014
86,84886,68818,27719,004
19,743
20,473
21,156

16.0
15.7
15.4
15.1
14.9

69.5
69.2
69.0
68.7
68.4

14.6
15.1
15.6
16.2
16.7

2000
2001
2002
2003
2004

126,892
127,100
127,286
127,447
127,581

18,602
18,452
18,335
18,262
18,23086,41986,03985,65285,281
84,977

21,87022,60923,29923,90524,373

14.7
14.5
14.4
14.3
14.3

68.1
67.7
67.3
66.9
66.6

17.2
17.8
18.3
18.8
19.1

2005
2006
2007
2008
2009

127,684
127,752
127,782
127,772
127,719

18,235
18,257
18,27318,30318,30684,44383,747
83,01782,32381,60325,00625,74826,492
27,14527,810

14.3
14.3
14.3
14.3
14.3

66.1
65.6
65.0
64.4
63.9

19.6
20.2
20.7
21.2
21.8

2010
2011
2012
2013
2014

127,623
127,481
127,292
127,056
126,773

18,31018,277
18,227
18,156
18,06081,18780,89379,83478,69177,54728,12628,311
29,23230,20931,166

14.3
14.3
14.3
14.3
14.2

63.6
63.5
62.7
61.9
61.2

22.0
22.2
23.0
23.8
24.6

2015
2016
2017
2018
2019

126,444
126,068
125,648
125,184
124,679

17,93917,791
17,62017,427
17,21776,62275,85675,211
74,67074,23631,88332,42132,81733,08733,226

14.2
14.1
14.0
13.9
13.8

60.6
60.2
59.9
59.6
59.5

25.2
25.7
26.1
26.4
26.6

2020
2021
2022
2023
2024

124,133
123,551
122,934
122,287
121,612

16,993
16,76016,522
16,284
16,04973,80573,426
73,11572,76272,36233,33533,36533,29733,242
33,202

13.7
13.6
13.4
13.3
13.2

59.5
59.4
59.5
59.5
59.5

26.9
27.0
27.1
27.2
27.3

2025
2026
2027
2028
2029

120,913120,193
119,454
118,699
117,930

15,821
15,604
15,40015,21015,03871,976
71,59071,16970,68670,152

33,11632,99932,88632,80332,740

13.1
13.0
12.9
12.8
12.8

59.5
59.6
59.6
59.6
59.5

27.4
27.5
27.5
27.6
27.8

2030
2031
2032
2033
2034

117,149
116,357
115,557
114,748
113,934

14,882
14,743
14,622
14,516
14,42569,50069,134
68,393
67,63566,82932,76832,48032,542
32,59732,680

12.7
12.7
12.7
12.7
12.7

59.3
59.4
59.2
58.9
58.7

28.0
27.9
28.2
28.4
28.7

2035
2036
2037
2038
2039

113,114112,290
111,462
110,632
109,800

14,347
14,28014,221
14,166
14,11565,98165,06864,102
63,086
62,09032,78732,94233,13933,37933,595

12.7
12.7
12.8
12.8
12.9

58.3
57.9
57.5
57.0
56.5

29.0
29.3
29.7
30.2
30.6

2040
2041
2042
2043
2044

108,964
108,125
107,285
106,443
105,601

14,062
14,006
13,945
13,876
13,79961,17660,32359,557
58,834
58,17133,726
33,79633,78233,733
33,631

12.9
13.0
13.0
13.0
13.1

56.1
55.8
55.5
55.3
55.1

31.0
31.3
31.5
31.7
31.8

2045
2046
2047
2048
2049

104,758
103,915
103,065
102,211
101,354

13,712
13,616
13,51013,394
13,27057,54956,99056,44755,90855,38333,49733,31033,10932,90932,701

13.1
13.1
13.1
13.1
13.1

54.9
54.8
54.8
54.7
54.6

32.0
32.1
32.1
32.2
32.3

2050

100,496

13,13954,90432,454

13.1

54.6

32.3

114

Shigesato TAKAHASHI, Ryuichi KANEKO, Akira ISHIKAWA,
Masako IKENOUE and Fusami MITA

Table A-4 Selected age-structure index of future population,
1995–2050: Medium variant

(yr.)

(yr.)

1995
1996
1997
1998
1999

39.6
39.9
40.3
40.7
41.0

39.7
40.0
40.4
40.7
41.0

Defining Productive Age as 15–64 Years Old
ElderlyAge Dependency Ratio (%)
Children
Total
ChildrenOld-age
Ratio (%)
43.9
23.0
20.9
91.2
44.4
22.6
21.8
96.4
45.0
22.3
22.7
101.8
45.6
22.0
23.6
107.2
46.1
21.7
24.4
112.4

2000
2001
2002
2003
2004

41.3
41.6
42.0
42.3
42.5

41.3
41.6
41.9
42.1
42.4

46.8
47.7
48.6
49.4
50.1

21.5
21.4
21.4
21.4
21.5

25.3
26.3
27.2
28.0
28.7

117.6
122.5
127.1
130.9
133.7

47.5
47.9
48.4
48.8
49.3

30.3
30.0
29.7
29.5
29.2

17.2
17.9
18.6
19.4
20.0

56.7
59.7
62.7
65.7
68.6

2005
2006
2007
2008
2009

42.8
43.1
43.4
43.6
43.9

42.6
42.9
43.2
43.5
43.7

51.2
52.5
53.9
55.2
56.5

21.6
21.8
22.0
22.2
22.4

29.6
30.7
31.9
33.0
34.1

137.1
141.0
145.0
148.3
151.9

49.9
50.6
51.3
52.0
52.5

29.1
29.0
29.0
29.0
29.1

20.8
21.6
22.3
23.0
23.4

71.4
74.3
76.9
79.1
80.6

2010
2011
2012
2013
2014

44.1
44.4
44.6
44.8
45.0

43.9
44.2
44.5
44.9
45.2

57.2
57.6
59.4
61.5
63.5

22.6
22.6
22.8
23.1
23.3

34.6
35.0
36.6
38.4
40.2

153.6
154.9
160.4
166.4
172.6

53.3
54.5
55.6
56.6
57.6

29.2
29.4
29.6
29.8
29.9

24.2
25.1
26.0
26.8
27.7

82.8
85.3
87.9
90.1
92.5

2015
2016
2017
2018
2019

45.3
45.5
45.7
45.9
46.1

45.5
45.8
46.2
46.6
46.9

65.0
66.2
67.1
67.6
67.9

23.4
23.5
23.4
23.3
23.2

41.6
42.7
43.6
44.3
44.8

177.7
182.2
186.2
189.9
193.0

58.1
58.2
59.7
61.4
63.1

30.0
30.0
30.2
30.4
30.6

28.1
28.2
29.6
31.0
32.5

93.6
94.3
98.0
102.1
106.3

2020
2021
2022
2023
2024

46.3
46.4
46.6
46.8
47.0

47.3
47.7
48.0
48.3
48.7

68.2
68.3
68.1
68.1
68.1

23.0
22.8
22.6
22.4
22.2

45.2
45.4
45.5
45.7
45.9

196.2
199.1
201.5
204.1
206.9

64.3
65.2
65.7
66.1
66.1

30.7
30.7
30.6
30.5
30.3

33.6
34.5
35.1
35.6
35.8

109.7
112.5
114.9
116.9
118.4

2025
2026
2027
2028
2029

47.1
47.3
47.4
47.5
47.6

49.0
49.2
49.4
49.6
49.8

68.0
67.9
67.8
67.9
68.1

22.0
21.8
21.6
21.5
21.4

46.0
46.1
46.2
46.4
46.7

209.3
211.5
213.5
215.7
217.7

66.1
66.0
65.7
65.5
65.3

30.1
29.8
29.6
29.4
29.2

36.1
36.2
36.1
36.1
36.1

120.0
121.2
122.0
122.9
123.9

2030
2031
2032
2033
2034

47.7
47.8
47.9
48.0
48.1

50.0
50.1
50.2
50.3
50.4

68.6
68.3
69.0
69.7
70.5

21.4
21.3
21.4
21.5
21.6

47.1
47.0
47.6
48.2
48.9

220.2
220.3
222.6
224.6
226.6

65.1
64.9
64.7
64.7
64.8

29.0
28.8
28.7
28.6
28.6

36.1
36.1
36.1
36.1
36.2

124.6
125.2
125.7
126.3
126.9

2035
2036
2037
2038
2039

48.1
48.2
48.2
48.3
48.3

50.5
50.6
50.6
50.6
50.5

71.4
72.6
73.9
75.4
76.8

21.7
21.9
22.2
22.5
22.7

49.7
50.6
51.7
52.9
54.1

228.5
230.7
233.0
235.6
238.0

65.2
64.9
65.4
66.0
66.8

28.6
28.5
28.6
28.8
28.9

36.6
36.3
36.8
37.3
37.8

127.9
127.4
128.5
129.5
130.7

2040
2041
2042
2043
2044

48.3
48.4
48.4
48.4
48.5

50.5
50.4
50.3
50.2
50.1

78.1
79.2
80.1
80.9
81.5

23.0
23.2
23.4
23.6
23.7

55.1
56.0
56.7
57.3
57.8

239.8
241.3
242.3
243.1
243.7

67.6
68.7
69.8
71.2
72.5

29.2
29.4
29.7
30.0
30.3

38.5
39.3
40.2
41.2
42.2

132.0
133.5
135.2
137.2
139.2

2045
2046
2047
2048
2049

48.5
48.5
48.5
48.6
48.6

50.0
50.0
49.9
49.9
49.9

82.0
82.3
82.6
82.8
83.0

23.8
23.9
23.9
24.0
24.0

58.2
58.4
58.7
58.9
59.0

244.3
244.6
245.1
245.7
246.4

73.7
74.7
75.4
76.1
76.6

30.6
30.8
31.0
31.2
31.3

43.1
43.8
44.4
44.9
45.3

140.7
142.1
143.0
143.9
144.5

2050

48.6

49.9

83.0

23.9

59.1

247.0

77.0

31.4

45.6

145.0

Year

Mean Age Median Age

Defining Productive Age as 20–69 Years Old
ElderlyAge Dependency Ratio (%)
Children
Total
ChildrenOld-age
Ratio (%)
47.6
33.6
14.0
41.5
47.3
32.7
14.6
44.5
47.1
32.0
15.2
47.5
47.1
31.3
15.8
50.6
47.3
30.8
16.5
53.6

Population Projections for Japan: Methods, Assumptions and Results

115

Table A-5 Trends and prospects of number of births, deaths,
and natural increase: Medium variant
Year

Crude number (1,000)

Crude rates (%)

BirthDeathsNatural increase

Birth

DeathsNatural increase

1996
1997
1998
1999

1,220
1,221
1,225
1,231

911
927
952
978

309
294
273
253

9.7
9.7
9.7
9.7

7.2
7.3
7.5
7.7

2.4
2.3
2.2
2.0

2000
2001
2002
2003
2004

1,239
1,246
1,251
1,254
1,254

1,004
1,031
1,059
1,087
1,115

235
215
193
168
139

9.7
9.8
9.8
9.8
9.8

7.9
8.1
8.3
8.5
8.7

1.8
1.7
1.5
1.3
1.1

2005
2006
2007
2008
2009

1,251
1,245
1,236
1,225
1,212

1,144
1,173
1,203
1,233
1,263

107
71
33
–8
–51

9.8
9.7
9.7
9.6
9.5

9.0
9.2
9.4
9.7
9.9

0.8
0.6
0.3
–0.1
–0.4

2010
2011
2012
2013
2014

1,198
1,182
1,164
1,146
1,128

1,293
1,323
1,353
1,382
1,410

–95
–141
–188
–235
–282

9.4
9.3
9.2
9.0
8.9

10.1
10.4
10.6
10.9
11.2

–0.7
–1.1
–1.5
–1.9
–2.2

2015
2016
2017
2018
2019

1,109
1,090
1,072
1,054
1,038

1,438
1,465
1,491
1,516
1,540

–329
–374
–418
–461
–502

8.8
8.7
8.6
8.5
8.4

11.4
11.7
11.9
12.2
12.4

–2.6
–3.0
–3.3
–3.7
–4.0

2020
2021
2022
2023
2024

1,022
1,008
995
985
977

1,563
1,585
1,606
1,626
1,644

–542
–578
–611
–641
–667

8.3
8.2
8.1
8.1
8.1

12.7
12.9
13.1
13.4
13.6

–4.4
–4.7
–5.0
–5.3
–5.5

2025
2026
2027
2028
2029

970
965
961
959
957

1,661
1,677
1,691
1,704
1,716

–691
–712
–730
–745
–759

8.1
8.1
8.1
8.1
8.2

13.8
14.0
14.2
14.5
14.7

–5.7
–6.0
–6.1
–6.3
–6.5

2030
2031
2032
2033
2034

956
954
953
951
949

1,727
1,736
1,743
1,749
1,753

–771
–782
–791
–798
–804

8.2
8.3
8.3
8.3
8.4

14.8
15.0
15.2
15.4
15.5

–6.6
–6.8
–6.9
–7.0
–7.1

2035
2036
2037
2038
2039

946
942
937
931
924

1,755
1,756
1,754
1,751
1,747

–810
–814
–818
–820
–823

8.4
8.4
8.5
8.5
8.5

15.6
15.8
15.9
15.9
16.0

–7.2
–7.3
–7.4
–7.5
–7.6

2040
2041
2042
2043
2044

916
907
898
887
877

1,742
1,737
1,729
1,720
1,710

–826
–829
–831
–832
–833

8.5
8.5
8.4
8.4
8.4

16.1
16.2
16.2
16.3
16.3

–7.6
–7.7
–7.8
–7.9
–8.0

2045
2046
2047
2048
2049

866
854
843
832
822

1,699
1,690
1,685
1,678
1,670

–833
–835
–842
–846
–848

8.3
8.3
8.3
8.2
8.2

16.3
16.4
16.5
16.6
16.6

–8.0
–8.1
–8.2
–8.3
–8.4

2050

812

1,661

–849

8.1

16.7

–8.5